icehawk2006

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Forum: Armchair-GMJul 19 at 5:48
Thread: Sigh
Forum: Armchair-GMJul 18 at 7:43
Thread: Sigh
Forum: Armchair-GMJun 22 at 11:22
<div class="quote"><div class="quote_t">Quoting: <b>Klara</b></div><div>1. So you know, since I've continuing to work on this, the fundamental problem was actually that oZS was being drastically over-scaled. That whole point was to remove the correlation between CF% and oZS, which you will be glad to know changes many scores.

2. I have since stoppped using oiS and oiSV and started using SCF% I didn't do this because its relation to the goalie, as both stats were used rel to the team. I changed it because of the low sample size.

3. It was a small project, got an 87% but don't plan to stop working on it.

4. Maybe I was too harsh on hockeyviz, some of their graphs are useful, but I was really wanting to see the actual numbers, because I am interested in creating various metrics, which obviously I can't do by judging the thickness of the bars. There is no me trying to find a specific result, after all, its the same data, Natural stat trick is more of the site I'm looking for, they have both graphics and the actual data to those graphics. Natural stat trick has by game all the data one could ask for. There is some useful visuals on hockeyviz, notably shooting maps, but I don't believe they paint the full picture.

5. I think we are not really connecting on individual stat, my understanding was that you were not referring to on ice stats (CF, FF, etc.), which are usually categorized differently than individual stats (iCF, P, etc).

6. I started this project after getting frustrated with looking at <a href="https://frozenpool.dobbersports.com/frozenpool_playerusage.php" rel="nofollow noreferrer noopener" target="_blank">https://frozenpool.dobbersports.com/frozenpool_playerusage.php</a>, which seems to be a very helpful tool, but I couldn't stand that there was no scaling on Corsi, which its common sense that if you start in the O zone more you are going to have a higher CF% than if you started more in the D zone. You could also see that for many players their GF% was drastically different than their CF%, even if the goalies are very different. But obviously GF% doesn't really have a very good sample size, especially for players who only played a few games, one of the reasons that I switched away from oiS and oiSV, so I went with SCF% because typically there is around 9x more data.

<img class="for_img" src="https://cdn.discordapp.com/attachments/636231620013195294/712684883289440327/1.PNG" alt="1.PNG">
newScore2 here is very simply CF%*SCF%/50. Obviously there is a small correlation between them, enough to change many scores.

<img class="for_img" src="https://cdn.discordapp.com/attachments/636231620013195294/712684880391307324/2.PNG" alt="2.PNG">
This was my solution, if you can tell me if there is a problem with that, I would actually appreciate it.

the next step would be to scale it by the quality of competition, newScore + sigma[playerScore*TOI]/(Total TOI) - 50.

<img class="for_img" src="https://cdn.discordapp.com/attachments/636231620013195294/712688933624086616/unknown.png" alt="unknown.png">

since this is what this whole deep dive down this stupid ass rabbit hole started from, the point is basically to solve what is wrong with this graph, for example, Thornton has a pretty good 53% CF, but he starts more in the oZone and faces easier competition than the rest of the team, so obviously his score should be worse than that, while Vlasic for example starts with a 49% CF but plays in the Defensive zone more and faces harder competition, and then there is just the fundamental problem of that Corsi (and Fenwick) don't consider the quality of the shots, hence the inclusion of SCF% and previously the rel difference of oiS and oiSV.

still no clue where you got the idea that I'm purposefully weighing things differently to fit a narrative... but you do you.

Unfortunately, I have not seen many things like this, especially with zone start scaling, and surprisingly quality of competition stats (QoC) seems to be hard to come by as well. I'm not re-inventing the wheel, im using it... its not rocket science.</div></div>

Just seeing this now. I've been mourning no more Sharks hockey.

A couple quick comments. I wouldn't assume more OZ starts means more CF. Couture for example, iso'ed, gets buried in CF even if he starts in the OZ, because he cant win a FO. Also, a lot of these dont account for FO zone locations in the OZ. Under the Scatter plots, I cant see the entirety of that image, feel like I am missing something. OZ starts and DZ starts dont carry the same weight for most teams, I cant tell where you account for that...
Forum: Armchair-GMMay 20 at 9:48
<div class="quote"><div class="quote_t">Quoting: <b>Klara</b></div><div>Don't know why you are still here, this is from a while ago.

All of this is stats that I use for myself and is one iteration of many that I created for a University project. oiSV% is compared to team oiSV% as a basic metric of shot quality, everything there is based of of an original CF% metric of 49.14. I am not saying that I would rather have Vlasic over a Karlsson over a Theodore or Letang, I'm using this as a basic metric to see how well the player performs at 5v5. This does not factor in Pk% or PP% and is simply a basis to determine if when the player is on the ice, are they getting more value, I don't care if you don't like it.

For the idea that you are basing everything off of Corsi, that's exactly what this chart is addressing. It factors in other things other than just looking at Corsi (or Fenwick), I just changed it so that &gt;50 is + and &lt;50 is negative purely so that it would be easier to graph. Of course, since this is basic, it does not really address line mates, and a few other extreme errors.

hockeyviz doesn't have what I'm looking for, and honestly, and I don't care for their fancy graphs, unless I can see the numbers and work with them, it isn't useful for me.

Also, the whole point of the stat is to ignore isolated stats and look to see how the team is affected with him on the ice, Corsi is not a personal stat, I could factor in personal stats to create a more advanced metric, but that's not the point of this one.

Please put your own stuff together if you would like to create an argument using numbers rather than looking at a fancy looking graph on a website that really doesn't say much. if you mention xG I might just throw up.</div></div>

Lololol. You’re taking basic data and manipulating it to fit your own narrative, talk about throwing up. Stats 101: weighting certain statistics to drive a result you want to see, bad. Here’s an idea, also from stats 101, let the data speak for itself. Also stats 101, if your output shows a vastly different picture than what the raw data is telling you, your model has a significant error somewhere. You’re model not only disagrees with the raw data, it disagrees with just about every assessment made by every expert in the field. Also basic research 101, if your model won’t pass peer review, it’s wrong. Your model will not pass peer review.

You really need to give the advanced stats gig up. The fact you don’t understand that corsi is an individual players impact on team shooting rates, same for fenwick, etc is largely hilarious. You even said it in your own words that it’s an individual stat.

Isolated stats are the only way to properly address player performance in comparison to other players! That’s why it’s exceptionally important to NOT include stats like team 5v5 sv%, because the stat is almost exclusively influenced by the goaltenders ability to make a save!! This is not rocket science. Ignoring isolated stats, while ranking Vlasic in comparison to other’s (that’s what we call an isolated comparison by the way)

All of my stats were even strength referenced. You’re telling me just because I don’t like it... while I don’t like or dislike it, it’s just wrong, and comically so, and you don’t like that, based on the basics, I’m telling you it’s entirely wrong. That’s some straight up irony right there.

The reference to hockeyviz was to get you to give up this fool’s errand and go to a proven source. No need to reinvent the wheel. Also saying “it doesn’t have what I want”, bad statistician, basically an admission you’re looking for a specific result. Yikes. Their “fancy” charts, all exclusively numbers based and have numbers based axis, from an experienced statistician, yeah totally not what you need. Yikes.

So I’m not going to put my own stuff together because 1) not rocket science 2) I do this kind of analytics every damn day at work all day 3) there’s no reason to with dozens of sources everywhere 4) the raw data is almost exclusively simple enough and has enough integrity that you don’t need to meld them into a model to get a picture of darn good fidelity.

If this is a university project you will fail. I am not joking, find something else.
Forum: Armchair-GMMay 13 at 12:18
Forum: Armchair-GMMay 13 at 12:01
<div class="quote"><div class="quote_t">Quoting: <b>Klara</b></div><div><img class="for_img" src="https://cdn.discordapp.com/attachments/636231620013195294/704484202971660328/Marc-Edouard_Vlasic_5v5_Effectivness.png" alt="Marc-Edouard_Vlasic_5v5_Effectivness.png">

This model represents a player's effectiveness at 5v5 based off of their CF, CA, oiS%, oiSV%, oZS, Team 5v5 S%, and Team 5v5 SV%, basically if you are positive then you are an effective 5v5 player, you produce more and or better opportunities than you give up. This year (so far) he had a score of +11.62. Far from his career high, but that puts him ahead of defensemen like Letang (+10.70), Erik Karlsson (+10.60), Shea Theodore (+8.87), Ryan McDonagh (+10.94), Erik Johnsson (+6.93), Zach Werenski(+5.57), Oliver Ekman-Larson(+5.02), and you get the point. Out of Sharks players who played most of the season that only puts him behind Hertl, Couture, Marleau(who had a great year according to the model), Goodrow, and Burns. That puts him ahead, of Karlsson, Kane, Dillon, Meier, Labanc, etc.

Over his career he has been a dominant 5v5 player, this is his worst year in a decade (haven't calculated before 09-10), but he is nowhere even close to buyout territory.

If a team doesn't want to acquire Vlasic oh well, the sharks should not move him and ABSOLUTELY should not buy him out.</div></div>

This is a terrible chart, all the data is wrong, it incorporates stats that shouldnt remotely be included in a player assessment (aka team 5v5 sv%, which is pretty much exclusively a goalie stat) and it doesn't take into account isolated stats. To even remotely think that Vlasic is on the same level as Theodore, Letang, or even Karlsson is sheer insanity. To think he was remotely in the top third of all Sharks players is also insanity, just straight crap.

Speaking of bad data, lets just look at 19-20. 5v5 CF% 49.14 (that's a minus on the chart, relative to the rest of team also bad. He was worse defensively 5v5 than Burns, who isnt even a D man, and thats while being carried by Erik Karlsson, his on ice sv% was lower than anyone but one person with more than 100 min TOI, so that should be a negative on your chart. in fact all of his relative stats are negative. He's at best a third pair defensemen, but yeah, keep trying to fall on that sword...
Forum: Armchair-GMAug 28, 2019 at 9:21
Forum: Armchair-GMAug 21, 2019 at 1:47
Forum: Armchair-GMAug 21, 2019 at 10:54
Forum: Armchair-GMAug 21, 2019 at 12:12
Thread: Nylander